An Enhanced Method for Information Hiding Using LSB Steganography

Sasmal, Milan; Mula, Debasmita

doi:10.1088/1742-6596/1797/1/012015

Cited by 6 publications

(3 citation statements)

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“…LSB technique is commonly used due to its simplicity in implementation which makes it efficient, but a recent study conducted by [29], established that there are lots of decoding algorithms available for its steganalysis by guessing the location where the secret message is embedded on the cover medium. The study gave a simplified demonstration to Least-Significant Bit (LSB) technique by using the following string of bytes to represent part of a digital image cover 10000100 10000110 100001001 10001101 01111001 01100101 01001010 00100110.…”

Section: Least Significant Bit (Lsb)mentioning

confidence: 99%

Reversible Image Steganography: A Review of Existing GAN-based Models

Nzewata,

Awodele,

Idowu

et al. 2022

CTICTR

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Image steganography is the method of concealing information, which can be text, image, or video, under a cover image in a way that it is invisible to the human eyes. Payload capacity, security and robustness are the features of steganography. A high-quality image steganography ensures a large payload capacity, superior security, and robustness against adversarial attacks. Image steganography is considered to be reversible if the concealed information's original state can be restored with little or no loss in the pixel values and textures. The main goal of this paper is to look at some of the typical techniques and models that are used to build image steganography systems by adopting the Preview, Question, Read, Summarize (PQRS) method to explain how the payload capacity, security, and robustness of these models may be quantified for future research and recommend GAN-based deep learning methods for improving existing reversible image steganography models. Keywords: Image steganography, GAN-based models, Payload capacity, PSNR, Reversibility, SSIM

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Section: Least Significant Bit (Lsb)mentioning

confidence: 99%

Reversible Image Steganography: A Review of Existing GAN-based Models

Nzewata,

Awodele,

Idowu

et al. 2022

CTICTR

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“…Steganography conceals the message while watermarking certifies its integrity, and cryptography scrambles it. In Sasmal & Mula (2021) the case of steganography, the sender must select a suitable message carrier before beginning the concealment process. A reliable steganographic method must be chosen to encrypt real information effectively.…”

Section: Introductionmentioning

confidence: 99%

An efficient and secure technique for image steganography using a hash function

Nezami

Ali

Asif

et al. 2022

PeerJ Computer Science

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Steganography is a technique in which a person hides information in digital media. The message sent by this technique is so secret that other people cannot even imagine the information’s existence. This article entails developing a mechanism for communicating one-on-one with individuals by concealing information from the rest of the group. Based on their availability, digital images are the most suited components for use as transmitters when compared to other objects available on the internet. The proposed technique encrypts a message within an image. There are several steganographic techniques for hiding hidden information in photographs, some of which are more difficult than others, and each has its strengths and weaknesses. The encryption mechanism employed may have different requirements depending on the application. For example, certain applications may require complete invisibility of the key information, while others may require the concealment of a larger secret message. In this research, we proposed a technique that converts plain text to ciphertext and encodes it in a picture using up to the four least significant bit (LSB) based on a hash function. The LSBs of the image pixel values are used to substitute pieces of text. Human eyes cannot predict the variation between the initial Image and the resulting image since only the LSBs are modified. The proposed technique is compared with state-of-the-art techniques. The results reveal that the proposed technique outperforms the existing techniques concerning security and efficiency with adequate MSE and PSNR.

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“…This method depends on the machine learningrule-basedd (RBML) and OR algorithms (OMR). The RBML algorithm was initially constructed and then students were simulated in the last T/F bladder examination, detected and marked based upon the co-circles [5].…”

Section: Introductionmentioning

confidence: 99%

Data Hiding by Unsupervised Machine Learning Using Clustering K-mean Technique

2021

IJCCCE

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Steganography includes hiding text, image, or any sentient information inside another image, video, or audio. It aims to increase individuals’ use of social media, the internet and web networks to securely transmit information between sender and receiver and an attacker will not be able to detect its information. The current article deals with steganography that can be used as machine learning method, it suggests a new method to hide data by using unsupervised machine learning (clustering k-mean algorithm). This system uses hidden data into the cover image, it consists of three steps: the first step divides the cover image into three clusterings that more contrast by using k-means cluster, the selects a text or image to be converted to binary by using ASCII code, the third step hides a binary message or binary image in the cover image by using sequential LSB method. After that, the system is implemented. The objective of the suggested system is obtained, using Unsupervised Machine Learning (K-mean technique) to securely send sensitive information without worrying about man-in-the-middle attack was proposed. Such a method is characterized by high security and capacity. Through evaluation, the system uses PSNR, MSE, Entropy, and Histogram to hide the secret message and secret image in the spatial domain in the cover image. Index Terms— Steganography, (LSB), K-mean, Cluster, Machine learning.

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An Enhanced Method for Information Hiding Using LSB Steganography

Cited by 6 publications

References 0 publications

Reversible Image Steganography: A Review of Existing GAN-based Models

Reversible Image Steganography: A Review of Existing GAN-based Models

An efficient and secure technique for image steganography using a hash function

Data Hiding by Unsupervised Machine Learning Using Clustering K-mean Technique

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